Data Acquisition

Leads: Emma Lundberg (PI), Nevan Krogan (PI), Prashant Mali (PI).

The Data Acquisition Module will generate comprehensive datasets for 100 chromatin modifiers and 100 metabolic enzymes involved in cancer, neuropsychiatric, and cardiac disorders across ethnicities and sexes. Data will be acquired in the triple-negative breast cancer cell line MDA-MB-468, including upon treatment with paclitaxel or ribociclib, and in two iPSC lines in the undifferentiated state as well as in differentiated neurons and cardiomyocytes using complementary mapping approaches. Proteomic mass spectrometry will be utilized to map protein-protein interactions of chromatin modifiers. Cellular imaging will map the spatial subcellular organization of key genes, their interactors and key signaling molecules involved in cancer and iPSC differentiation. Genetic perturbation screens via CRISPR/Cas9 will assess the transcriptome-wide impact of gene perturbations and unravel mechanisms contributing to the maintenance of cell identity. Together, these data will provide a comprehensive dataset to inform AI/ML research on systematic genotype-phenotype mapping.